Privatized machine learning using generative adversarial networks
US-2019244138-A1 · Aug 8, 2019 · US
US12425844B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12425844-B2 |
| Application number | US-202018018236-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 30, 2020 |
| Priority date | Jul 30, 2020 |
| Publication date | Sep 23, 2025 |
| Grant date | Sep 23, 2025 |
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The present specification relates to a method and a device for randomizing a signal that satisfies ε-differential privacy, the method receiving a signal having a specific value of a bit error rate (BER), and generating a randomized signal on the basis of the signal, and then transmitting the randomized signal to a machine learning server. If a differential privacy mechanism is provided in a physical layer, true randomness of a wireless channel causes security to be less vulnerable than that of a pseudo random mechanism provided by an application, communication delay is reduced, and the power of the device can be reduced.
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What is claimed is: 1. A method for signal randomization, the method performed by a communication apparatus and comprising: receiving a random access preamble from a serving cell; transmitting a random access response to the serving cell; receiving a signal from the serving cell, wherein the signal haves a bit error rate (BER) of a first value; generating a randomized signal based on the signal; and transmitting the randomized signal to a machine learning server, wherein the randomized signal is generated based on BER measurement and decoding, wherein the randomized signal includes a bit in which an error has not occurred due to the BER of the first value and a bit in which an error has occurred due to the BER of the first value. 2. The method of claim 1 , wherein the bit in which the error has not occurred is included in the randomized signal without change, wherein the bit in which the error has occurred is changed to 0 or 1 based on a BER of a second value and included in the randomized signal. 3. The method of claim 2 , wherein the BER of the first value and the BER of the second value are determined based on a transmission power of the signal. 4. The method of claim 2 , wherein the BER of the second value is determined based on iterative decoding. 5. The method of claim 2 , wherein the BER of the first value and the BER of the second value are determined based on a modulation and coding scheme (MCS) of the signal. 6. The method of claim 2 , wherein the BER of the second value is determined based on retransmission of the signal. 7. The method of claim 1 , wherein the randomized signal is generated in a physical layer of the communication apparatus, wherein the randomized signal is directly transmitted from the physical layer to an application layer. 8. The method of claim 1 , wherein the randomized signal satisfies ε-differential privacy. 9. The method of claim 1 , wherein the decoding is iterative decoding. 10. A communication apparatus comprising: one or more memories to store instructions; one or more transceivers; and one or more processors coupling the one or more memories and the one or more transceivers, wherein the one or more processors execute the instructions for: receiving a random access preamble from a serving cell; transmitting a random access response to the serving cell; receiving a signal from the serving cell, wherein the signal haves a bit error rate (BER) of a first value; generating a randomized signal based on the signal; and transmitting the randomized signal to a machine learning server, wherein the randomized signal is generated based on BER measurement and decoding, wherein the randomized signal includes a bit in which an error has not occurred due to the BER of the first value and a bit in which an error has occurred due to the BER of the first value. 11. An apparatus configured to control a communication apparatus, the apparatus comprising: one or more processors; and one or more memories executablely coupled by the one or more processors and storing instructions, wherein the one or more processors execute the instructions for: receiving a random access preamble from a serving cell; transmitting a random access response to the serving cell; receiving a signal from the serving cell, wherein the signal haves a bit error rate (BER) of a first value; generating a randomized signal based on the signal; and transmitting the randomized signal to a machine learning server, wherein the randomized signal is generated based on BER measurement and decoding, wherein the randomized signal includes a bit in which an error has not occurred due to the BER of the first value and a bit in which an error has occurred due to the BER of the first value.
Random access procedures, e.g. with 4-step access · CPC title
Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII] · CPC title
Iterative decoding, including iteration between signal detection and decoding operation · CPC title
Details of error rate determination, e.g. BER, FER or WER · CPC title
in wireless communication networks · CPC title
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